Initial Presenting Symptoms, Comorbidities and Severity of COVID-19 Patients Attending Hmawbi and Indine Treatment Centers During the Second Wave of Epidemic in Myanmar: a Cross-sectional Study

Ye Minn Htun (  dryeminnhtun85@gmail.com ) Health and Disease Control Unit https://orcid.org/0000-0002-9706-9834 Tun Tun Win Department of Preventive and Social Medicine, Defence Services Medical Academy Aung Aung Department of Research and Development, Defence Services Medical School Thant Zin Latt Department of Research and Development, Defence Services Medical School Yan Naung Phyo Outpatient Department, No.3 Military Hospital (100 bedded) Thet Min Tun Department of Preventive and Social Medicine, Defence Services Medical Academy Nyan Sint Htun Department of Preventive and Social Medicine, Defence Services Medical Academy Kyaw Myo Tun Department of Preventive and Social Medicine, Defence Services Medical Academy Khin Aung Htun Department of Surgery, Defence Services Medical Academy


Background
In early December 2019, the rst pneumonia cases of unknown origin were identi ed in Wuhan, the capital city of Hubei province [1]. Since then, there has been a rapid spread of the virus in China and other countries, leading to a global public health problem. On 30th January 2020, the World Health Organization (WHO) has announced coronavirus disease 2019 (COVID-19) as a public health emergency of international concern [2]. After increasing the rapid spread of con rmed cases and continuing the risk of further global spread, the WHO declared COVID-19 as a pandemic on 11th March 2020. Since then, Europe and America had become the epicenter of the pandemic with more con rmed cases and deaths than the rest of the world [3].
The COVID-19 was a highly contagious infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), belonging to an enveloped β-coronavirus genus [4,5]. Host cell binding and entry were mediated by the spike (S) protein of the viral envelope. The S1 subunit of the S protein contained the receptor-binding domain that bound to the peptidase domain of the angiotensin-converting enzyme 2 (ACE2) receptor. SARS-CoV-2 had a greater a nity for the upper respiratory tract, thus could infect the upper respiratory tract and conducted airways more easily [6,7].
The SARS-CoV-2 virus was primarily transmitted from infected people to others who were in close contact through respiratory droplets, by direct contact with infected persons, or by contact with contaminated objects and surfaces [8][9][10]. The airborne transmission might be possible in speci c settings in which procedures that generate aerosols were performed [11]. The clinical spectrum of COVID-19 could range from asymptomatic infection or mild upper respiratory tract illness to severe interstitial pneumonia with respiratory failure. The common symptoms were fever or chills, cough, shortness of breath, fatigue, muscle aches, headache, loss of taste or smell, sore throat, runny nose, nausea or vomiting, and diarrhea [1]. During the pre-symptomatic period, some infected persons could be contagious and therefore, people infected with COVID-19 could transmit the virus before signi cant symptoms developed [12,13].
Certain comorbidities (including diabetes, heart diseases, chronic kidney disease, and obesity) were strongly related to COVID-19 hospitalization and severity. Some studies demonstrated that comorbidities including hypertension, diabetes, and cardiovascular diseases, chronic lung diseases, chronic kidney disease, and cancer might be predictors for the poor prognosis in COVID-19 patients [14]. Older people with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer were more at risk of developing a serious illness and required referral for intensive care due to their low immune status [1,[15][16][17][18][19].
As of 7th March 2021, the total number of con rmed cases was 116 million with approximately 2.5 million deaths in 219 countries and territories around the world [20]. In Myanmar, the rst COVID-19 reported cases were identi ed on 23rd March 2020 and the total con rmed cases were 142,023 with 3,200 deaths through 7th March 2021. The con rmed cases were increasingly reported in Yangon Region followed by Mandalay, Bago, Ayeyarwaddy, and Rakhine State [21,22]. To control the disease spread, the government performed mitigating measures such as an increase in testing capacity, expansion of treatment centers and quarantine facilities, restriction of public gatherings, closing international ights, closing restaurants and daycare facilities [22].
Although focusing on the public health measures like social distancing, the prohibition of public gatherings, and increased use of face masks to control the spread of COVID-19, these measures alone were uncertain to stop the pandemic due to the highly contagious nature of the disease. The continuation of learning more about the natural course of COVID-19, clinical presentation, comorbidity, and severity of disease was critical for healthcare system preparedness [23,24]. To better understand and adequately manage this novel threat, exploring detailed knowledge on clinical courses of infected patients and clarifying the severity were required [25]. The aim of the study has therefore been to identify initial presenting symptoms, comorbidities, and severity of COVID-19 patients in Treatment Centers.

Study design and population
A cross-sectional study was conducted among COVID-19 patients attending at Hmawbi and Indine Treatment Centers from November to December 2020. All patients with con rmed SARS-CoV-2 infection by a positive result on reverse transcription polymerase chain reaction (RT-PCR) testing of a nasopharyngeal sample were included in this study.

Study area
The study was carried out at Hmawbi and Indine Treatment Centers, which provided the medical services to the con rmed COVID-19 patients, established in the second wave of the COVID-19 epidemic in Myanmar. The Treatment Centers were located in Hamwbi and Hlegu Townships, Yangon Region, Myanmar.

Sample size determination and sampling technique
The sample size was calculated using a single population proportion formula [26] with an assumption of 95% Con dence Intervals (CI), 7% margin of error, and 33.9% of COVID-19 patients with comorbidity were severe [27]. Base on this assumption, the nal sample size was estimated as 176. All adult COVID-19 patients attending at two COVID-19 Treatment Centers during the study period were selected. The patients who were transferred to an intensive care unit and those who did not give informed consent were excluded.

Operational de nition
Current smoking was de ned as an adult who has smoked 100 cigarettes in his or her lifetime and who currently smokes cigarettes. Alcohol drinking was de ned as an adult who took at least 12 drinks in the past year but 3 drinks or fewer per week, on average over the past year. A contact person was de ned as a person who experienced any one of the following exposures during the 2 days before and the 14 days after the onset of symptoms of a probable or con rmed case: face-to-face contact with a probable or con rmed case within 1 meter and for more than 15 minutes, direct physical contact with a probable or con rmed case, and direct care for a patient with probable or con rmed COVID-19 disease without using proper personal protective equipment [28]. Comorbidity was a presence of more or additional medical conditions or diseases in COVID-19 patients. The presenting symptom was a symptom or group of symptoms about which the COVID-19 patient initially complains or from which he/she sought relief (such as fever, muscle ache, cough, sore throat, dyspnoea, etc.,). The severity of COVID-19 was de ned as an adult patient with clinical signs of pneumonia (fever, cough, dyspnoea, fast breathing) [28] which was diagnosed by a physician and radiologist, and it was categorized as pneumonia and no pneumonia.

Data collection and procedure
The data were collected by three interviewers through telephone survey method using a structured questionnaire that included personal characteristics (sex, age, state and region, township, education, occupation, height, weight, body mass index (BMI), smoking status, alcohol drinking, contact with known COVID-19 cases, travelling history to abroad, and travelling history to townships under stay at home order), comorbidity (hypertension, diabetes mellitus, coronary heart disease, chronic respiratory disease, cerebrovascular accident, cirrhosis of liver, hepatitis B virus infection, hepatitis C virus infection, chronic kidney disease, haematological disease, and cancer), and initial presenting symptoms (fever, chills, di culty in breathing, fatigue, muscle aches, headache, loss of smell, loss of taste, sore throat, runny nose, nausea or vomiting, diarrhea). The outcome variable, severity (pneumonia) of COVID-19 patients, was reviewed from patients' records. The participants were explained about the purpose of the study and then a telephone survey was conducted after receiving verbal informed consent.

Statistical analysis
The collected data were entered into Microsoft Excel 2016 and exported to IBM SPSS Statistics for Windows, Version 23.0. (Armonk, NY: IBM Corp) for analysis. Descriptive statistics were presented as frequency and percentages for categorical variables and mean (standard deviation, SD) for continuous variables. Bivariable logistic regression analysis was performed to assess the relative impact of the predictor variables on the outcome variable. To control for potential confounding factors, multivariable logistic regression analysis was performed. All independent factors of bivariable regression analysis were candidates for the multivariable logistic regression model. The results of group comparisons of risk factors and pneumonia were expressed as Adjusted Odds Ratio (AOR) with 95% CI and a p value was set at < 0.05 for statistical signi cance.

Results
A total of 176 COVID-19 patients were included in the study. Table 1 showed the demographic characteristics of COVID-19 patients. Among them, 87 (49.4%) were female and 89 (50.6%) were male. The mean (± SD) age was 42.52 (± 16.34) years with a range of 18-86 years and 150 (85.2%) patients were younger than 60 years. Most of the patients, 164 (93.2%), were from Yangon Region and among them, 116 (70.7%) patients were from North District. In total, 78 (44.3%) patients had a high school education level and 105 (59.7%) patients were employed. In BMI of patients, 112 (63.6%) were healthy or normal weight, 36 (20.5%) were overweight and 10 (5.7%) were obese. Thirteen (7.4%) patients were current smokers and 10 (5.7%) had a history of alcohol drinking. Overall, 63 (35.8%) patients had a history of contact with con rmed cases. Only two (1.1%) and 4 (2.3%) patients travelled to foreign countries and townships under stay at home order, respectively. The initial presenting symptoms, comorbidities and severity of COVID-19 were described in Table 2   BMI was classi ed as < 25 kg/m 2 (underweight and normal weight) and ≥ 25 kg/m 2 (overweight and obese).

Discussion
The COVID-19 mainly affects the respiratory system, and some patients required intensive care due to a rapid progression of hypoxia, pneumonia, and acute respiratory distress syndrome. This study investigated the prevalence of symptomatic, comorbidities, and severity, and the associated factors of severity in COVID-19 patients. In this study, the sex distribution was not too different and it was in line with the studies done in China [19,29]. The recent study reported that (14.8%) of patients were the older age and it seemed to be consistent with the nding obtained in the China study (12.3%) [19] and lower than the studies conducted in the USA (28.3%) [30] and Germany (26.7%) [31]. More than one-fourth of the patients (26.2%) were overweight or obese in this study and this result was lower than the ndings of studies done in Thailand (32.9%) [32], Germany (38.2%) [31], and China (47.5%) [33]. The reason for these variations might be due to the difference in the socio-economic and geographical nature of the study area, variation in sample size, and distinction in lifestyle factors.
The prevalence of initial presenting symptoms (76.7%) in the current study was lower than studies done in Thailand (94.8%) [32] and Korea (91.3%) [34], but higher than in the China study (70.6%) [19]. This inconsistency might be due to variation of diagnostic and hospitalization criteria of COVID-19 patients. One explanation for the detection of nearly one-fourth of the asymptomatic patients in this study might be due to well achievement in case nding, contact tracing, and surveillance of COVID-19 cases by the healthcare providers. A substantial number of undocumented infections leading to no symptoms might enable the rapid spread of SARS-CoV-2 [35]. In Myanmar, the government expanded the testing capacity for primary contacts and imported cases as a priority of testing. All COVID-19 patients including symptomatic and asymptomatic who were con rmed by RT-PCR and Standard Q COVID-19 Antigen Rapid Diagnosis Test were hospitalized in designated hospitals. In the current study, it was surprising that loss of smell, apart from fever and cough, was one of the most common symptoms, and this nding was contrary to that of previous studies done in the same constitution reported that fatigue, sore throat, shortness of breath and rhinorrhea were the most common presenting symptoms [30,[32][33][34]36].
The prevalence of comorbid diseases (35.8%) in COVID-19 patients was higher than the ndings of the studies conducted in China (15.8%) [19] and Thailand (25.0%) [32]. This discrepancy could be attributed to variation in the prevalence of chronic diseases across age, gender distribution, and geographic region. Non-communicable diseases (NCDs) were identi ed as a priority public health problem in Myanmar and cardiovascular disease was one of the NCDs with the highest impact on mortality [37]. Over 2012 to 2017, most of the admitted patients with NCDs were middle and older aged population with the median and interquartile range of 39 (25-55) years and (51.6%) of those were males [38]. In the current study, the most common comorbidities were hypertension and diabetes mellitus and these results supported the ndings of the earlier studies conducted in hospitalized COVID-19 patients [19,30,31,34,36].
As the severity of COVID-19, the prevalence of pneumonia in this study was (23.3%) and it was agreed with the nding of other study revealed that (23.6%) of the COVID-19 patients developed pneumonia [31].
However, it was lower than the results of the studies conducted in Thailand (38.9%) [32], Korea (73.2%) [34], and China (67.9%) [19] and (83.5%) [29], respectively. It was possible that these results were due to variability of chest imaging ndings (chest radiograph or computerized tomography), the difference in criteria of patient isolation and hospitalization, and contrast to protocol and management guidelines of COVID-19 patients. The symptomatic patients tend to have severe in ammation in the lungs, which more commonly leads to disease progression. The symptomatic patients had a higher risk of developing bilateral pneumonia and less likely to show improvement of pneumonia than asymptomatic patients [19].
In the recent study, age was a signi cant determinant of pneumonia in COVID-19 patients and it might be explained by the fact that older people were particularly susceptible to develop more infections as natural immunity declined gradually at older ages. Another explanation for this nding could be that the older people might have more expression of ACE2 encoded by the ACE2 gene and have other conventional factors such as reduced immunity, poor organ function, or coexisting comorbid diseases which might have increased risk of disease severity [39]. This nding was keeping with the previous studies done in Thailand [32], China [29,33,36], and Korea [34] reported that older age was a potential predictive factor of pneumonia in SARS-CoV-2 infected patients.
The immune function and response in viral infections were in uenced by lifestyle factors, overweight or obesity. This study con rmed that overweight or obesity was associated with the development of pneumonia in COVID-19 patients. The possible reason might be due to the fact that people with overweight or obesity might have comorbidities including metabolic diseases, cardiovascular diseases, and cancers that were susceptible to infection. Moreover, they had a signi cantly large amount of ACE2 receptor in adipose tissue and were more likely to SARS-CoV-2 infection, which resulted in increased viral shedding, immune inactivation, and cytokine storm [40]. This nding also supported the evidence from other studies conducted in Thailand [32], China [33], Korea [34], and Germany [31] reported that overweight or obesity patients were more likely to get pneumonia than normal weight patients.
Tobacco contains components that disrupt the normal epithelial lining of the respiratory system leading to increased oxidative injury and impairment of mucociliary clearance [41]. Smoking was also a signi cant predictor of pneumonia in COVID-19 patients in the current study. This could be because tobacco smoke suppressed the function of innate immune cells, including respiratory epithelium, alveolar surfactant, macrophage, neutrophils, and lymphocytes. This could make smokers were more susceptible to develop the complications of COVID-19, such as pneumonia. This result matched those observed in earlier studies done in China [42,43] and Turkey [44] reported that there was an association between the current smoking status and disease severity of COVID-19. However, this nding was contrary to previous studies which had evidence that smoking was not associated with the severity of COVID-19 [34,36,45].
The COVID-19 patients with a history of alcohol drinking were more likely to develop pneumonia than those who were non-drinkers. A possible explanation for this might be alcohol-induced oxidative stress leading to depletion of the critical antioxidant glutathione and deterioration of alveolar barrier integrity and modulation of the immune response [46]. Alcohol also had a negative impact on lung innate defense and response to lung injury with an impairment of the ability to ght infection [47]. In addition, alcohol consumption lead to over expression of ACE2 receptors, which could support the facilitated proliferation of SARS-CoV-2 into the cells [48]. This nding was accorded with the results of other studies conducted in USA [47] and Denmark [49].
There were some limitations in this study. Firstly, it was relatively di cult to establish a causal relationship between severity and independent variables due to the cross-sectional nature of this study. A longitudinal study with a larger sample size could be applied to nd out the higher strength of association. Secondly, although the results were representative of the population with the same demographic characteristics, further research using a random sampling method should be conducted to have a more representative cohort. Thirdly, the asymptomatic patients might have developed symptoms later and they could be over looked. Lastly, the patients with unrecognized or unknown comorbidity would not be detected and therefore, further studies should obtain more information about the existing unrecognized comorbid diseases in order to ascertain association.

Conclusions
In conclusion, approximately one-fourth of asymptomatic patients with test positive for COVID-19 were identi ed, and therefore, screening, surveillance and contact tracing should be more expand for early detection of asymptomatic people and rapid control of community spread. The prevalence of comorbidity and severity (pneumonia) in COVID-19 patients were (35.8%) and (23.3%), respectively. This study reapproved the association of demographic factors and lifestyle factors with the severity of COVID-19. Therefore, the healthcare providers should pay particular attention to the COVID-19 patients who were aged 60 years and older, overweight or obese, current smokers, and alcohol drinkers to detect and reduce the disease severity as early as possible. Firstly, all participants were explained about study by telephone before conducting survey and informed about their right of withdrawing the study without restriction whenever necessary. The verbal informed consent was obtained from each participant before collecting data. The agreement of participation in the study was retained by phone recording. Privacy and con dentiality of information obtained from the participants were maintained throughout the study process.

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